Solid Focal Liver Lesions Research Articles

Enhancing gadoxetic acid–enhanced liver MRI: a synergistic approach with deep learning CAIPIRINHA-VIBE and optimized fat suppression techniques

ObjectiveTo investigate whether a deep learning (DL) controlled aliasing in parallel imaging results in higher acceleration (CAIPIRINHA)-volumetric interpolated breath-hold examination (VIBE) technique can improve image quality, lesion conspicuity, and lesion detection compared to a standard CAIPIRINHA-VIBE technique in gadoxetic acid–enhanced liver MRI.MethodsThis retrospective single-center study included 168 patients who underwent gadoxetic acid–enhanced liver MRI at 3 T using both standard CAIPIRINHA-VIBE and DL CAIPIRINHA-VIBE techniques on pre-contrast and hepatobiliary phase (HBP) images. Additionally, high-resolution (HR) DL CAIPIRINHA-VIBE was obtained with 1-mm slice thickness on the HBP. Three abdominal radiologists independently assessed the image quality and lesion conspicuity of pre-contrast and HBP images. Statistical analyses involved the Wilcoxon signed-rank test for image quality assessment and the generalized estimation equation for lesion conspicuity and detection evaluation.ResultsDL and HR-DL CAIPIRINHA-VIBE demonstrated significantly improved overall image quality and reduced artifacts on pre-contrast and HBP images compared to standard CAIPIRINHA-VIBE (p < 0.001), with a shorter acquisition time (DL vs standard, 11 s vs 17 s). However, the former presented a more synthetic appearance (both p < 0.05). HR-DL CAIPIRINHA-VIBE showed superior lesion conspicuity to standard and DL CAIPIRINHA-VIBE on HBP images (p < 0.001). Moreover, HR-DL CAIPIRINHA-VIBE exhibited a significantly higher detection rate of small (< 2 cm) solid focal liver lesions (FLLs) on HBP images compared to standard CAIPIRINHA-VIBE (92.5% vs 87.4%; odds ratio = 1.83; p = 0.036).ConclusionDL and HR-DL CAIPIRINHA-VIBE achieved superior image quality compared to standard CAIPIRINHA-VIBE. Additionally, HR-DL CAIPIRINHA-VIBE improved the lesion conspicuity and detection of small solid FLLs. DL and HR-DL CAIPIRINHA-VIBE hold the potential clinical utility for gadoxetic acid–enhanced liver MRI.Clinical relevance statementDL and HR-DL CAIPIRINHA-VIBE hold promise as potential alternatives to standard CAIPIRINHA-VIBE in routine clinical liver MRI, improving the image quality and lesion conspicuity, enhancing the detection of small (< 2 cm) solid focal liver lesions, and reducing the acquisition time.Key Points• DL and HR-DL CAIPIRINHA-VIBE demonstrated improved overall image quality and reduced artifacts on pre-contrast and HBP images compared to standard CAIPIRINHA-VIBE, in addition to a shorter acquisition time.• DL and HR-DL CAIPIRINHA-VIBE yielded a more synthetic appearance than standard CAIPIRINHA-VIBE.• HR-DL CAIPIRINHA-VIBE showed improved lesion conspicuity than standard CAIPIRINHA-VIBE on HBP images, with a higher detection of small (< 2 cm) solid focal liver lesions.

Usefulness of Breath-Hold Fat-Suppressed T2-Weighted Images With Deep Learning-Based Reconstruction of the Liver: Comparison to Conventional Free-Breathing Turbo Spin Echo.

The aim of this study was to evaluate the usefulness of breath-hold turbo spin echo with deep learning-based reconstruction (BH-DL-TSE) in acquiring fat-suppressed T2-weighted images (FS-T2WI) of the liver by comparing this method with conventional free-breathing turbo spin echo (FB-TSE) and breath-hold half Fourier single-shot turbo spin echo with deep learning-based reconstruction (BH-DL-HASTE). The study cohort comprised 111 patients with suspected liver disease who underwent 3 T magnetic resonance imaging. Fifty-eight focal solid liver lesions ≥10 mm were also evaluated. Three sets of FS-T2WI were acquired using FB-TSE, prototypical BH-DL-TSE, and prototypical BH-DL-HASTE, respectively. In the qualitative analysis, 2 radiologists evaluated the image quality using a 5-point scale. In the quantitative analysis, we calculated the lesion-to-liver signal intensity ratio (LEL-SIR). Friedman test and Dunn multiple comparison test were performed to assess differences among 3 types of FS-T2WI with respect to image quality and LEL-SIR. The mean acquisition time was 4 minutes and 43 seconds ± 1 minute and 21 seconds (95% confidence interval, 4 minutes and 28 seconds to 4 minutes and 58 seconds) for FB-TSE, 40 seconds for BH-DL-TSE, and 20 seconds for BH-DL-HASTE. In the qualitative analysis, BH-DL-HASTE resulted in the fewest respiratory motion artifacts ( P < 0.0001). BH-DL-TSE and FB-TSE exhibited significantly less motion-related signal loss and clearer intrahepatic vessels than BH-DL-HASTE ( P < 0.0001). Regarding the edge sharpness of the left lobe, BH-DL-HASTE scored the highest ( P < 0.0001), and BH-DL-TSE scored higher than FB-TSE ( P = 0.0290). There were no significant differences among 3 types of FS-T2WI with respect to the edge sharpness of the right lobe ( P = 0.1290), lesion conspicuity ( P = 0.5292), and LEL-SIR ( P = 0.6026). BH-DL-TSE provides a shorter acquisition time and comparable or better image quality than FB-TSE, and could replace FB-TSE in acquiring FS-T2WI of the liver. BH-DL-TSE and BH-DL-HASTE have their own advantages and may be used complementarily.

Differential diagnosis of different types of solid focal liver lesions using two-dimensional shear wave elastography.

BACKGROUNDThe clinical management and prognosis differ between benign and malignant solid focal liver lesions (FLLs), as well as among different pathological types of malignant FLLs. Accurate diagnosis of the possible types of solid FLLs is important. Our previous study confirmed the value of shear wave elastography (SWE) using maximal elasticity (Emax) as the parameter in the differential diagnosis between benign and malignant FLLs. However, the value of SWE in the differential diagnosis among different pathological types of malignant FLLs has not been proved.AIMTo explore the value of two-dimensional SWE (2D-SWE) using Emax in the differential diagnosis of FLLs, especially among different pathological types of malignant FLLs.METHODSAll the patients enrolled in this study were diagnosed as benign, malignant or undetermined FLLs by conventional ultrasound. Emax of FLLs and the periphery of FLLs was measured using 2D-SWE and compared between benign and malignant FLLs or among different pathological types of malignant FLLs.RESULTSThe study included 32 benign FLLs in 31 patients and 100 malignant FLLs in 96 patients, including 16 cholangiocellular carcinomas (CCCs), 72 hepatocellular carcinomas (HCCs) and 12 liver metastases. Thirty-five FLLs were diagnosed as undetermined by conventional ultrasound. There were significant differences between Emax of malignant (2.21 ± 0.57 m/s) and benign (1.59 ± 0.37 m/s) FLLs (P = 0.000), and between Emax of the periphery of malignant (1.52 ± 0.39 m/s) and benign (1.36 ± 0.44 m/s) FLLs (P = 0.040). Emax of liver metastases (2.73 ± 0.99 m/s) was significantly higher than that of CCCs (2.14 ± 0.34 m/s) and HCCs (2.14 ± 0.46 m/s) (P = 0.002). The sensitivity, specificity and accuracy were 71.00%, 84.38% and 74.24% respectively, using Emax > 1.905 m/s (AUC 0.843) to diagnose as malignant and 23 of 35 (65.74%) FLLs with undetermined diagnosis by conventional ultrasound were diagnosed correctly.CONCLUSIONMalignant FLLs were stiffer than benign ones and liver metastases were stiffer than primary liver carcinomas. 2D-SWE with Emax was a useful complement to conventional ultrasound for the differential diagnosis of FLLs.

Value of shear wave elastography with maximal elasticity in differentiating benign and malignant solid focal liver lesions.

BACKGROUNDIt is important to differentiate benign and malignant focal liver lesions (FLLs) accurately. Despite the wide use and acceptance of shear wave elastography (SWE), its value for assessing the elasticity of FLLs and differentiating benign and malignant FLLs is still investigational. Previous studies of SWE for FLLs used mean elasticity as the parameter to reflect the stiffness of FLLs. Considering the inhomogeneity of tumor stiffness, maximal elasticity (Emax) might be the suitable parameter to reflect the stiffness of FLLs and to differentiate malignant FLLs from benign ones.AIMTo explore the value of SWE with Emax in differential diagnosis of solid FLLs.METHODSWe included 104 solid FLLs in 95 patients and 50 healthy volunteers. All the subjects were examined using conventional ultrasound (US) and virtual touch tissue quantification(VTQ) imaging. A diagnosis of benign or malignant FLL was made using conventional US. Ten VTQ values were acquired after 10 consecutive measurements for each FLL and each normal liver, and the largest value was recorded as Emax.RESULTSThere were 56 cases of malignant FLLs and 48 cases of benign FLLs in this study. Emax of malignant FLLs (3.29 ± 0.88 m/s) was significantly higher than that of benign FLLs (1.30 ± 0.46 m/s, P < 0.01) and that of livers in healthy volunteers (1.15 ± 0.17 m/s, P < 0.01). The cut-off point of Emax was 1.945, and the area under the curve was 0.978. The sensitivity and specificity of Emax were 92.9% and 91.7%, respectively, higher (but not significantly) than those of conventional US (80.4% for sensitivity and 81.3% for specificity). Combined diagnosis of conventional US and Emax using parallel testing improved the sensitivity to 100% with specificity of 75%.CONCLUSIONSWE is a convenient and easy method to obtain accurate stiffness information of solid FLLs. Emax is useful for differential diagnosis of FLLs, especially in combination with conventional US.

Value of gadoxetic acid-enhanced MR imaging and DWI in classification, characterization and confidence in diagnosis of solid focal liver lesions

Objective To assess gadoxetic acid (Gd-EOB-DTPA) and diffusion-weighted imaging (DWI) value in classification (benign vs. malignant) and characterization of solid focal liver lesions (SFLLs) and impact on confidence in diagnosis. Methods A total of 195 lesions (46 hepatocellular carcinomas [HCCs], 45 metastases, 32 adenomas, 37 focal nodular hyperplasias [FNHs] and 35 hemangiomas) were retrospectively evaluated in 93 patients. Three imaging datasets were compared: DWI/ apparent diffusion coefficient (ADC) (set A), Gd-EOB-DTPA (set B) and combination of both (set C). Two radiologists (R) independently classified (on a five-point ordinal scale) and characterized each lesion. The accuracy in classification and characterization was compared, and the diagnostic confidence was assessed. Results The classification accuracy on set A, B and C was 86.2%, 91.3% and 91.8% (R1), and 84.6%, 91.8% and 93.3% (R2); and characterization accuracy was 67.2%, 88.2% and 87.7% (R1), and 60.5%, 88.2% and 85.6% (R2). Classification by reader 1 showed no significant difference between set A and B (p=.09). For both readers, there was a significant difference between set A and C in both classification and characterization (all p < .05), but no significant difference between set B and C in neither classification nor characterization. No significant difference between the three datasets in classification and characterization of hemangiomas (all p > .05). The diagnostic confidence of the readers has increased progressively from set A to Set C (all p < .01). Conclusions DWI may suggest benignity or malignancy of solid liver lesions, while Gd-EOB-DTPA-enhanced imaging remains superior in lesions characterization and the combination of both increases the diagnostic confidence. DWI is very helpful in the diagnosis of hepatic hemangiomas.

Assessment of SE-MRE-derived shear stiffness at 3.0 Tesla for solid liver tumors characterization.

To evaluate the feasibility and diagnostic value of using a 2D spin-echo MR elastography (SE-MRE) sequence at 3.0 Tesla for solid focal liver lesions (FLL) characterization. This prospective study included 55 patients with solid FLL (size > 20mm), who underwent liver SE-MRE at 3 Tesla between 2016 and 2019. Stiffness measurements were performed by two independent readers blinded to the complete MRI exam or patient information. Histological confirmation or typical behavior on the complete MRI exam evaluated in consensus by expert abdominal radiologists was used as reference standard. FLLs were grouped and compared (malignant vs. benign) using the Mann-Whitney and Kruskal-Wallis tests. MRE diagnostic performance was assessed, and stiffness cutoffs were obtained by analysis of ROC curves from accuracy maximization. A linear regression plot was used to evaluate inter-rater agreement for FLLs stiffness measurements. p values < 0.05 were considered statistically significant. The final study group comprised 57 FLLs (34 malignant, 23 benign). Stiffness measurements were technically successful in 91.23% of lesions. To both readers, the median stiffness of the lesions categorized as benign was 4.5 ± 1.5kPa and in the malignant group 6.8 ± 1.7 and 7.5 ± 1.5kPa depending on the reader. A cutoff of 5.8kPa distinguished malignant and benign lesions with 88% specificity and 75-85% accuracy depending on the reader. The inter-rater agreement was 0.90 ± 0.04 with a correlation coefficient of 0.94. 2D-SE-MRE at 3.0 T provides high specificity and PPV to differentiate benign from malignant liver lesions. Trial registration 18FFUA-A02.

A Comprehensive Narrative Review on the Evolving Role of Endoscopic Ultrasound in Focal Solid Liver Lesions Diagnosis and Management.

The implications of endoscopic ultrasound (EUS) have expanded considerably in recent years to cover more fields in invasive gastroenterology practice, as both an investigative and therapeutic modality. The utility of EUS in the diagnosis and management of focal liver lesions has gained a special attractiveness recently. The EUS probe proximity to the liver and its excellent spatial resolution enables real-time images coupled with several enhancement techniques, such as contrast-enhanced (CE) EUS. Aside from its notable capability to execute targeted biopsies and therapeutic interventions, EUS has developed into a hopeful therapeutic tool for the management of solid liver lesions. Herein, we provide a comprehensive state-of-the-art review on the efficacy and safety of EUS in the diagnosis and management of focal solid liver lesions. Medline/PubMed and Embase database searches were conducted by two separate authors (T.K. and W.S.), all relevant studies were assessed, and relevant data was extracted and fully reported. EUS-guided diagnosis of focal liver lesions by sonographic morphologic appearance and cytological and histopathological finding of biopsies obtained via fine needle aspiration/biopsy have been shown to significantly improve the diagnosis of solid liver lesions compared with traditional imaging tools. Similarly, EUS-guided treatment has been shown to consistently have excellent technical success, high efficacy, and minor adverse events. The evolving valuable evidences of EUS utility might satisfy the unmet need of optimizing management of focal solid liver lesions.

Deep learning for differentiation of benign and malignant solid liver lesions on ultrasonography.

The ability to reliably distinguish benign from malignant solid liver lesions on ultrasonography can increase access, decrease costs, and help to better triage patients for biopsy. In this study, we used deep learning to differentiate benign from malignant focal solid liver lesions based on their ultrasound appearance. Among the 596 patients who met the inclusion criteria, there were 911 images of individual liver lesions, of which 535 were malignant and 376 were benign. Our training set contained 660 lesions augmented dynamically during training for a total of 330,000 images; our test set contained 79 images. A neural network with ResNet50 architecture was fine-tuned using pre-trained weights on ImageNet. Non-cystic liver lesions with definite diagnosis by histopathology or MRI were included. Accuracy of the final model was compared with expert interpretation. Two separate datasets were used in training and evaluation, one with all lesions and one with lesions deemed to be of uncertain diagnosis based on the Code Abdomen rating system. Our model trained on the complete set of all lesions achieved a test accuracy of 0.84 (95% CI 0.74-0.90) compared to expert 1 with a test accuracy of 0.80 (95% CI 0.70-0.87) and expert 2 with a test accuracy of 0.73 (95% CI 0.63-0.82). Our model trained on the uncertain set of lesions achieved a test accuracy of 0.79 (95% CI 0.69-0.87) compared to expert 1 with a test accuracy of 0.70 (95% CI 0.59-0.78) and expert 2 with a test accuracy of 0.66 (95% CI 0.55-0.75). On the uncertain dataset, compared to all experts averaged, the model had higher test accuracy (0.79 vs.0.68, p = 0.025). Deep learning algorithms proposed in the current study improve differentiation of benign from malignant ultrasound-captured solid liver lesions and perform comparably to expert radiologists. Deep learning tools can potentially be used to improve the accuracy and efficiency of clinical workflows.

Evaluation of Solid Focal Liver Lesions by Shear Wave Sonoelastography with FNAC Correlation

Benign vs. malignant hepatic lesions could be differentiated using a cut off value of 25 kPa. The overall sensitivity & specificity of SWE was found to be 66% and 30% respectively as a standalone technique, however the predicative accuracy of SWE in conjunction with gray scale sonographic findings was 91.4%.

Late Gadolinium Hyperintensity of Suspected Colorectal Liver Metastases on Gadofosveset-Enhanced Magnetic Resonance Imaging: A Predictor of Benignity and a Potential Problem-Solving Tool

PurposeLate gadolinium hyperintensity (LGH) is sometimes seen in colorectal liver metastasis (CRLM) and represents a significant diagnostic pitfall due to overlap with LGH in benign hemangiomas; therefore, the objective of this study was to determine the prevalence of LGH and the ability of LGH to differentiate between CRLM and benign lesions with intravascular (gadofosveset) vs extracellular contrast agents (gadobutrol). MethodsPatients with known colorectal cancer and suspected liver lesions were prospectively recruited into this institutional review board–approved, single institution study and received magnetic resonance imaging of the liver with gadofosveset and gadobutrol. The prevalence of LGH for CRLMs and solid benign lesions was determined. Receiver operating characteristics curves were determined for the presence of LGH as a predictor of benignity. The utility of LGH to differentiate between CRLM and solid benign lesions using gadofosveset vs gadobutrol was compared using the generalized estimating equation. ResultsTwenty-five patients with 131 solid focal liver lesions were recruited. The prevalence of LGH of CRLMs was 11.2% (95% confidence interval [CI]: 0.5%–21.8%) with gadofosveset vs 63.7% (95% CI: 45.7%–81.7%) with gadobutrol. The area under the receiver operating characteristic curve for the presence of LGH as a predictor of benignity was 0.86 using gadofosveset vs 0.75 using gadobutrol. Both LGH (P = .003) and the interaction of contrast agent and LGH (P = .003) statistically significantly differentiated CRLM from benign lesions. ConclusionLGH is more common with extracellular than with intravascular contrast agents and is statistically significantly associated with benign lesions rather than metastases.

Abstract No. 497 Deep learning for differentiation of benign and malignant solid liver lesions on ultrasonography

Ultrasound-guided liver biopsy is commonly performed by interventional radiologists to diagnose solid liver lesions. However, the procedure is invasive and carries the risk of infection and bleeding. In this study, we used deep learning to differentiate benign from malignant focal solid liver lesions based on their appearance on routine abdominal ultrasound. A ResNet50-based neural network was fine-tuned using pre-trained weights on ImageNet. Patients who had abdominal ultrasound from 2014-2018 with liver code C2-C5 on Code Abdomen, an institutional lesion categorization system for abdominal organs on cross-sectional imaging modeled after BI-RADS, were included (Table 1). Non-cystic liver lesions with definite diagnosis by histopathology or MRI were included. Our dataset was split into training and validation sets by patient and augmented in real-time with zoom, skew, and flip transformations during training. Subgroup analysis of category 3 and 4 lesions (uncertain diagnosis set) was performed. Accuracy of the final model was compared with expert interpretation. Among the 410 patients who met the inclusion criteria, there were 521 images of individual lesions, of which 170 were malignant and 351 were benign. Our training set had 419 lesions and our validation set had 102 lesions. Our model achieved a validation accuracy of 83.3% compared to expert accuracy of 77.5% and 60.8%, respectively. The model had an ROC AUC of 0.83, sensitivity of 0.82, and specificity of 0.84. For the uncertain diagnosis set, our model achieved a validation accuracy of 85.1% compared to expert accuracy of 74.5% and 61.7%, respectively. The model had an ROC AUC of 0.78, sensitivity of 0.91, and specificity of 0.67. Deep learning distinguished benign from malignant ultrasound-captured solid liver lesions with a high accuracy compared to expert radiologists and can better triage patients for biopsy, particularly those at high risk or with multiple lesions.Table 1CategoryDescriptionBenign:MalignantBiopsy:MRI DiagnosisC2Benign157:01:15C3Indeterminate113:186:125C4Suspicious10:3416:28C5Highly suspicious2:7533:45 Open table in a new tab

High Acceleration Three-Dimensional T1-Weighted Dual Echo Dixon Hepatobiliary Phase Imaging Using Compressed Sensing-Sensitivity Encoding: Comparison of Image Quality and Solid Lesion Detectability with the Standard T1-Weighted Sequence.

ObjectiveTo compare a high acceleration three-dimensional (3D) T1-weighted gradient-recalled-echo (GRE) sequence using the combined compressed sensing (CS)-sensitivity encoding (SENSE) method with a conventional 3D GRE sequence using SENSE, with respect to image quality and detectability of solid focal liver lesions (FLLs) in the hepatobiliary phase (HBP) of gadoxetic acid-enhanced liver MRI.Materials and MethodsA total of 217 patients with gadoxetic acid-enhanced liver MRI at 3T (54 in the preliminary study and 163 in the main study) were retrospectively included. In the main study, HBP imaging was done twice using the standard mDixon-3D-GRE technique with SENSE (acceleration factor [AF]: 2.8, standard mDixon-GRE) and the high acceleration mDixon-3D GRE technique using the combined CS-SENSE technique (CS-SENSE mDixon-GRE). Two abdominal radiologists assessed the two MRI data sets for image quality in consensus. Three other abdominal radiologists independently assessed the diagnostic performance of each data set and its ability to detect solid FLLs in 117 patients with 193 solid nodules and compared them using jackknife alternative free-response receiver operating characteristics (JAFROC).ResultsThere was no significant difference in the overall image quality. CS-SENSE mDixon-GRE showed higher image noise, but lesser motion artifact levels compared with the standard mDixon-GRE (all p < 0.05). In terms of lesion detection, reader-averaged figures-of-merit estimated with JAFROC was 0.918 for standard mDixon-GRE, and 0.953 for CS-SENSE mDixon-GRE (p = 0.142). The non-inferiority of CS-SENSE mDixon-GRE over standard mDixon-GRE was confirmed (difference: 0.064 [−0.012, 0.081]).ConclusionThe CS-SENSE mDixon-GRE HBP sequence provided comparable overall image quality and non-inferior solid FFL detectability compared with the standard mDixon-GRE sequence, with reduced acquisition time.

CT reconstruction algorithms affect histogram and texture analysis: evidence for liver parenchyma, focal solid liver lesions, and renal cysts.

To determine the effects of different reconstruction algorithms on histogram and texture features in different targets. Among 3620 patients, 480 had normal liver parenchyma, 494 had focal solid liver lesions (metastases = 259; hepatocellular carcinoma = 99; hemangioma = 78; abscess = 32; and cholangiocarcinoma = 26), and 488 had renal cysts. CT images were reconstructed with filtered back-projection (FBP), hybrid iterative reconstruction (HIR), and iterative model reconstruction (IMR) algorithms. Computerized histogram and texture analyses were performed by extracting 11 features. Different reconstruction algorithms had distinct, significant effects. IMR had a greater effect than HIR. For instance, IMR had a significant effect on five features of liver parenchyma, nine features of focal liver lesions, and four features of renal cysts on portal-phase scans and four, eight, and four features, respectively, on precontrast scans (p < 0.05). Meanwhile, different algorithms had a greater effect on focal liver lesions (six in HIR and nine in IMR on portal-phase, three in HIR, and eight in IMR on precontrast scans) than on liver parenchyma or cysts. The mean attenuation and standard deviation were not affected by the reconstruction algorithm (p > .05). Most parameters showed good or excellent intra- and interobserver agreement, with intraclass correlation coefficients ranging from 0.634 to 0.972. Different reconstruction algorithms affect histogram and texture features. Reconstruction algorithms showed stronger effects in focal liver lesions than in liver parenchyma or renal cysts. • Imaging heterogeneities influenced the quantification of image features. • Different reconstruction algorithms had a significant effect on histogram and texture features. • Solid liver lesions were more affected than liver parenchyma or cysts.

The Prevalence of Hyperechoic Rim in Solid Focal Liver Lesions and Its Implication

The objective of this study was to investigate the prevalence and clinical implications of the hyperechoic rim of liver focal solid lesions. A retrospective review was conducted of sonograms of focal liver lesions with a hyperechoic rim, as well as relative examinations such as computed tomography, magnetic resonance imaging, biopsy, resection, and histopathology reports. A cohort of 10 232 patients was found to have solid focal liver lesions (2030 malignant, 8202 benign). A hyperechoic rim was determined in 182 hemangiomas, 2 granulomas, 2 hepatocellular carcinomas (HCCs), and 4 other malignancies. There were significant differences between malignant and benign lesions ( P &lt; .001), between HCCs and hemangiomas ( P &lt; .001), between malignancies and hemangiomas ( P &lt; .001), between HCCs and granulomas ( P = .044), and between other malignancies and granulomas ( P = .005). There was no significant difference between liver granulomas and hemangiomas ( P = .656). In this study, a hyperechoic rim in solid focal liver lesions appeared mainly in hemangiomas, granulomas, and rarely in malignant lesions.

Role of Acoustic Radiation Force Impulse Elastography in the Characterization of Focal Solid Hepatic Lesions.

Objective:The purpose of the study is to investigate the usefulness of acoustic radiation force impulse (ARFI) elastography in the characterization of focal solid liver lesions as benign, malignant, or metastatic using ARFI two-dimensional (2D) imaging and ARFI quantification (shear wave velocities [SWVs]).Materials and Methods:Sixty lesions were included in this study. The lesions were classified into three groups: Group I included benign lesions (n = 25), Group II included malignant lesions (n = 27), and Group III included metastatic lesions (n = 8). ARFI elastography was performed in all these patients using a Siemens ACUSON S 2000™ ultrasound machine. Stiffness and size of the lesions were assessed on ARFI 2D images in correlation with B-mode ultrasound images. SWVs were obtained in these lesions for the quantification of stiffness.Results:In ARFI 2D images, malignant lesions were predominantly stiffer and larger, while benign lesions were softer and similar in size (P < 0.05). The mean SWVs in benign, malignant, and metastatic lesions were 1.30 ± 0.35 m/s, 2.93 ± 0.75 m/s, and 2.77 ± 0.90 m/s, respectively. The area under receiver operating characteristic curve of SWV for differentiating benign from malignant lesions was 0.877, suggesting fair accuracy (95% confidence interval: 0.777–0.976); with a cutoff value of 2 m/s, showing sensitivity: 92%; specificity: 96%; positive predictive value: 96%; negative predictive value: 93% (P < 0.05). Statistically significant difference exists in SWV of benign and malignant or metastatic lesions.Conclusion:ARFI elastography with 2D imaging and quantification might be useful in the characterization of benign and malignant liver lesions.

A Model-Based Prediction of the Probability of Hepatocellular Adenoma and Focal Nodular Hyperplasia Based on Characteristics on Contrast-Enhanced Ultrasound

Contrast-enhanced ultrasound (CEUS) is an emerging imaging technique that is increasingly used to diagnose liver lesions. It is of the utmost importance to differentiate between the two most common solid focal liver lesions (i.e., hepatocellular adenoma [HCA] and focal nodular hyperplasia [FNH]), because their management and follow-up differ greatly. The main objective of this study was to determine how frequently the specific CEUS features of HCA and FNH are visible on CEUS and to define their predictive value for discrimination between HCA and FNH. We included 324 CEUS examinations performed on patients with FNH (n = 181) or HCA (n = 143). Patients with HCA and FNH significantly differed with respect to age and CEUS features of steatosis, echogenicity, homogeneity, the presence of a central scar, central artery, arterial enhancement pattern, necrosis or thrombus and enhancement in the late venous phase.

Textural Analysis of Liver Focal Lesions with Co-occurrence Matrix and Wavelet Transform on CT: A Feasible Study in FNH, HEM and HCC

Focal nodular hyperplasia (FNH), hepatocellular carcinoma (HCC) and cavernous hemangioma (HEM) are three types of solid focal liver lesions. Using CT images to identify these three types of lesions is the most commonly method. However, this method usually mainly depends on experiences. Whereas, more objective and quantitative image information could be explored with texture analysis method. This research aims to discuss the appreciations of texture analysis based on CT images for identifying FNH, HCC and HEM. This paper retrospectively analyzed 81 clinically or pathologically diagnosed cases, each of which contains contrast non-enhanced and contrast two-phasic enhanced CT images. The texture analysis was based on gray level co-occurrence matrix (GLCM) and wavelet transform. The results shows that the misclassification rates of texture classification were low to 2.73% between FNH and HEM (between benign lesions), 3.19% between FNH and HCC (between benign lesions and malignant lesions), and 1.67% between HEM and HCC (between benign lesions and malignant lesions) respectively. The effect of texture classification based on contrast two-phasic enhanced CT images was better than contrast non-enhanced CT images.

Contrast enhanced ultrasound features of hepatic cystadenoma and hepatic cystadenocarcinoma

Objective: Hepatic (biliary) cystic tumor (HBCT) is a rare focal cystic liver lesion, which has been rarely described in the literature. In our current multicenter, retrospective study, we aimed to analyze contrast enhanced ultrasound (CEUS) features and its diagnostic performance in histologically proved HBCT.Material and methods: Twenty-three patients with single HBCT were retrospectively analyzed. Histologically, 17 (73.9%) were benign hepatic (biliary) cystadenoma (HBCA), 6 (26.1%) were hepatic (biliary) cystadenocarcinoma (HBCAC). All CEUS examinations were assessed by two independent radiologists in consensus. Criteria of CEUS imaging evaluation included the contrast enhancement pattern of lesion (hypoenhancing, hyperenhancing, isoenhancing in comparison to the surrounding liver parenchyma) during the arterial, portal venous and late phases.Results: After injection of ultrasound contrast agents, most of the HBCTs (78.3%, 18/23) had typical honeycomb enhancement pattern of the cystic wall, septa or mural nodules. Comparing between HBCA and HBCAC, hyperenhancement of the honeycomb septa during the arterial phase was more common in HBCA (p = .047). However, hypoenhancement during the portal venous and late phases was the characteristic of HBCAC (p = .041).Conclusions: The EFSUMB algorithm for CEUS for characterization of solid focal liver lesions is also applicable to HBCT. CEUS evaluation can avoid further diagnostic investigations or invasive biopsy procedure.

Percutaneous real-time sonoelastography as a non-invasive tool for the characterization of solid focal liver lesions: A prospective study

BackgroundReal-time sonoelastography is currently used for the characterization of superficial solid lesions such as thyroid and breast masses. This study evaluates the usefulness of percutaneous sonoelastography for the characterization of solid focal liver lesions. Methods30 out of 43 patients with 38 known liver lesions were included in a prospective, diagnostic study. Qualitative analysis (pattern of deformation, elasticity type of liver tumour) and semi-quantitative measurements (strain ratio, hardness percentage, histogram) were evaluated. Sensitivity, specificity, positive and negative predictive values were calculated and the area under the receiver operating characteristics curve was constructed. ResultsPatterns A and C-D are specific of benign lesions and metastases respectively. The patterns for haemangiomas, focal nodular hyperplasia and metastases were significantly different to each other in terms of strain ratio, hardness percentage and histogram (p<0.05). A statistically significant difference (p<0.001) was observed between the median values of the 3 measured parameters for benign (1.02; 12%; 47) and malignant lesions (1.66; 65%; 20.5) respectively. The area under the receiver operating characteristics curve values for strain ratio, hardness percentage and histogram were 0.88, 0.89, and 0.86 respectively for cut-off values of 1.2, 45, and 30. ConclusionsBy percutaneous sonoelastography it is possible to differentiate benign versus malignant focal liver lesions, metastases in particular, with good diagnostic performance.

Characterization of fortuitously discovered focal liver lesions: additional information provided by shearwave elastography.

To prospectively assess the stiffness of incidentally discovered focal liver lesions (FLL) with no history of chronic liver disease or extrahepatic cancer using shearwave elastography (SWE). Between June 2011 and May 2012, all FLL fortuitously discovered on ultrasound examination were prospectively included. For each lesion, stiffness was measured (kPa). Characterization of the lesion relied on magnetic resonance imaging (MRI) and/or contrast-enhanced ultrasound, or biopsy. Tumour stiffness was analysed using ANOVA and non-parametric Mann-Whitney tests. 105 lesions were successfully evaluated in 73 patients (61 women, 84%) with a mean age of 44.8 (range: 20‒75). The mean stiffness was 33.3 ± 12.7 kPa for the 60 focal nodular hyperplasia (FNH), 19.7 ± 9.8 k Pa for the 17 hepatocellular adenomas (HCA), 17.1 ± 7 kPa for the 20 haemangiomas, 11.3 ± 4.3 kPa for the five focal fatty sparing, 34.1 ± 7.3 kPa for the two cholangiocarcinomas, and 19.6 kPa for one hepatocellular carcinoma (p < 0.0001). There was no difference between the benign and the malignant groups (p = 0.64). FNHs were significantly stiffer than HCAs (p < 0.0001). Telangiectatic/inflammatory HCAs were significantly stiffer than the steatotic HCAs (p = 0.014). The area under the ROC curve (AUROC) for differentiating FNH from other lesions was 0.86 ± 0.04. SWE may provide additional information for the characterization of FFL, and may help in differentiating FNH from HCAs, and in subtyping HCAs. • SWE might be helpful for the characterization of solid focal liver lesions • SWE cannot differentiate benign from malignant liver lesions • FNHs are significantly stiffer than other benign lesions • Telangiectatic/inflammatory HCA are significantly stiffer than steatotic ones.